A comprehensive study of multiplicative attribute graph model

dc.contributor.advisorMakowski, Armanden_US
dc.contributor.authorQu, Sikaien_US
dc.contributor.departmentElectrical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2016-06-22T06:10:19Z
dc.date.available2016-06-22T06:10:19Z
dc.date.issued2016en_US
dc.description.abstractGraphs are powerful tools to describe social, technological and biological networks, with nodes representing agents (people, websites, gene, etc.) and edges (or links) representing relations (or interactions) between agents. Examples of real-world networks include social networks, the World Wide Web, collaboration networks, protein networks, etc. Researchers often model these networks as random graphs. In this dissertation, we study a recently introduced social network model, named the Multiplicative Attribute Graph model (MAG), which takes into account the randomness of nodal attributes in the process of link formation (i.e., the probability of a link existing between two nodes depends on their attributes). Kim and Lesckovec, who defined the model, have claimed that this model exhibit some of the properties a real world social network is expected to have. Focusing on a homogeneous version of this model, we investigate the existence of zero-one laws for graph properties, e.g., the absence of isolated nodes, graph connectivity and the emergence of triangles. We obtain conditions on the parameters of the model, so that these properties occur with high or vanishingly probability as the number of nodes becomes unboundedly large. In that regime, we also investigate the property of triadic closure and the nodal degree distribution.en_US
dc.identifierhttps://doi.org/10.13016/M2JF50
dc.identifier.urihttp://hdl.handle.net/1903/18357
dc.language.isoenen_US
dc.subject.pqcontrolledElectrical engineeringen_US
dc.subject.pqcontrolledStatisticsen_US
dc.subject.pqcontrolledMathematicsen_US
dc.subject.pquncontrolledLog-normal degree distributionen_US
dc.subject.pquncontrolledModelingen_US
dc.subject.pquncontrolledRandom Graphsen_US
dc.subject.pquncontrolledSocial Networken_US
dc.subject.pquncontrolledZero-one lawsen_US
dc.titleA comprehensive study of multiplicative attribute graph modelen_US
dc.typeDissertationen_US

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